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This work builds on an existing model of discrete canonical evolution and applies it to the general case of a linear dynamical system, i.e., a finite-dimensional system with configuration space isomorphic to $ \mathbb{R}^{q} $ and linear…

Mathematical Physics · Physics 2021-06-30 Jakub Káninský

Modularized Koopman Bilinear Form (M-KBF) is presented to model and predict the transient dynamics of microgrids in the presence of disturbances. As a scalable data-driven approach, M-KBF divides the identification and prediction of the…

Systems and Control · Electrical Eng. & Systems 2022-05-19 Xinyuan Jiang , Yan Li , Daning Huang

The Koopman operator provides a linear perspective on non-linear dynamics by focusing on the evolution of observables in an invariant subspace. Observables of interest are typically linearly reconstructed from the Koopman eigenfunctions.…

Dynamical Systems · Mathematics 2024-03-06 Shaowu Pan , Karthik Duraisamy

Semi-supervised learning is an important and active topic of research in pattern recognition. For classification using linear discriminant analysis specifically, several semi-supervised variants have been proposed. Using any one of these…

Machine Learning · Statistics 2014-11-18 Jesse H. Krijthe , Marco Loog

We propose a model order reduction approach for balanced truncation of linear switched systems. Such systems switch among a finite number of linear subsystems or modes. We compute pairs of controllability and observability Gramians…

Numerical Analysis · Mathematics 2017-12-07 Ion Victor Gosea , Mihaly Petreczky , Athanasios C. Antoulas , Christophe Fiter

We say that two elements of a group or semigroup are $\Bbbk$-linear conjugates if their images under any linear representation over $\Bbbk$ are conjugate matrices. In this paper we characterize $\Bbbk$-linear conjugacy for finite semigroups…

Representation Theory · Mathematics 2019-11-13 Benjamin Steinberg

This paper proposes a unified family of learnable Koopman operator parameterizations that integrate linear dynamical systems theory with modern deep learning forecasting architectures. We introduce four learnable Koopman…

Machine Learning · Computer Science 2026-03-16 Ali Forootani , Raffaele Iervolino

Superintegrable systems are a class of physical systems which possess more conserved quantities than their degrees of freedom. The study of these systems has a long history and continues to attract significant international attention. This…

Mathematical Physics · Physics 2018-02-26 Md Fazlul Hoque

The properties of discrete nonlinear symmetries of integrable equations are investigated. These symmetries are shown to be canonical transformations. On the basis of the considered examples, it is concluded, that the densities of the…

High Energy Physics - Theory · Physics 2009-10-22 A. N. Leznov , A. V. Razumov

We consider the application of Koopman theory to nonlinear partial differential equations. We demonstrate that the observables chosen for constructing the Koopman operator are critical for enabling an accurate approximation to the nonlinear…

Pattern Formation and Solitons · Physics 2016-07-26 J. Nathan Kutz , Joshua L. Proctor , Steven L. Brunton

We establish the binary nonlinearization approach of the spectral problem of the super AKNS system, and then use it to obtain the super finite-dimensional integrable Hamiltonian system in supersymmetry manifold $\mathbb{R}^{4N|2N}$. The…

Exactly Solvable and Integrable Systems · Physics 2009-11-13 Jingsong He , Jing Yu , Ruguang Zhou , Yi Cheng

In the paper we investigate the theory of quantum optical systems. As an application we integrate and describe the quantum optical systems which are generically related to the classical orthogonal polynomials. The family of coherent states…

Mathematical Physics · Physics 2014-11-03 Maciej Horowski , Anatol Odzijewicz , Agnieszka Tereszkiewicz

A practical version of the polynomial canonical formalism is developed for normal mesoscopic systems consisting of N independent electrons. Drastic simplification of calculations is attained by means of proper ordering excited states of the…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 N. K. Kuzmenko , V. M. Mikhajlov

System representations inspired by the infinite-dimensional Koopman operator (generator) are increasingly considered for predictive modeling. Due to the operator's linearity, a range of nonlinear systems admit linear predictor…

Machine Learning · Computer Science 2022-05-31 Petar Bevanda , Max Beier , Sebastian Kerz , Armin Lederer , Stefan Sosnowski , Sandra Hirche

The Koopman operator is a mathematical tool that allows for a linear description of non-linear systems, but working in infinite dimensional spaces. Dynamic Mode Decomposition and Extended Dynamic Mode Decomposition are amongst the most…

Machine Learning · Computer Science 2021-03-26 Francesco Zanini , Alessandro Chiuso

Balanced truncation, a technique from robust control theory, is a systematic method for producing simple approximate models of complex linear systems. This technique may have significant applications in physics, particularly in the study of…

Quantum Physics · Physics 2007-05-23 Benjamin Rahn

Data-driven model predictive control based on Willems' fundamental lemma has proven effective for linear systems, but extending stability guarantees to nonlinear systems remains an open challenge. In this paper, we establish conditions…

Systems and Control · Electrical Eng. & Systems 2026-03-19 Amin Taghieh , SangWoo Park

In areas such as kernel smoothing and non-parametric regression there is emphasis on smooth interpolation and smooth statistical models. Splines are known to have optimal smoothness properties in one and higher dimensions. It is shown, with…

Computation · Statistics 2008-09-29 Ron A. Bates , Hugo Maruri-Aguilar , Henry P. Wynn

A large family of linear, usually overdetermined, systems of partial differential equations that admit a multiplication of solutions, i.e, a bi-linear and commutative mapping on the solution space, is studied. This family of PDE's contains…

Analysis of PDEs · Mathematics 2008-03-19 Jens Jonasson

In recent years, the success of the Koopman operator in dynamical systems analysis has also fueled the development of Koopman operator-based control frameworks. In order to preserve the relatively low data requirements for an approximation…

Optimization and Control · Mathematics 2020-10-15 Sebastian Peitz , Samuel E. Otto , Clarence W. Rowley